CN110674081A

CN110674081A - Student growth file management method, computer device and computer readable storage medium

Info

Publication number: CN110674081A
Application number: CN201910901643.6A
Authority: CN
Inventors: 郭启恩; 梁骏豪
Original assignee: Regional Computer Co Ltd
Current assignee: Regional Computer Co Ltd
Priority date: 2019-09-23
Filing date: 2019-09-23
Publication date: 2020-01-10

Abstract

The invention provides a management method of a student growth archive, a computer device and a computer readable storage medium, wherein the management method comprises the steps of face recognition, receiving picture signals and character signals uploaded by a user; extracting a face characteristic value in the picture signal; judging whether the face characteristic value is matched with the target identity signal; if the face characteristic value is matched with the target identity signal, extracting keywords in the character signal, and matching intelligent categories according to the keywords; adding an intelligent class to the target profile signal. Therefore, the information on the picture is acquired through face recognition, the face on the picture is recognized accurately and rapidly, the matched intelligent class is associated with the target after face recognition through extracting the keywords in the character signals added during picture uploading, the purpose of classifying the student files through the uploaded signals can be achieved simply and efficiently, and the error rate during classification is further reduced.

Description

Student growth file management method, computer device and computer readable storage medium

Technical Field

The invention relates to the field of archive management, in particular to a student growth archive management method, a computer device and a computer readable storage medium.

Background

With the progress of information technology, more and more schools begin to establish electronic chemistry student management systems, but the electronic chemistry student management systems are often used for information collection, school achievement collection and the like of students entering and leaving schools or dormitories, but still adopt non-intelligent means in the aspect of recording non-learning growth of students. For example, in the aspect of recording the personal growth of students by photos, when uploading photos, schools need to be equipped with relevant personnel to identify each student of the photos, the time consumption is high when the identified photos are stored in the archives of each corresponding student, the time consumption is high if people want to collect the information on the photos and then identify some places which are interested, good and bad for the students, and in addition, the photos are identified manually, so that errors are generated to a great extent.

Disclosure of Invention

The first objective of the present invention is to provide a management method capable of rapidly, efficiently and accurately classifying student growth files.

The second objective of the present invention is to provide a computer device for executing the above usage method.

A third object of the present invention is to provide a computer-readable storage medium for performing the above-described usage method.

In order to realize the first aim of the invention, the invention provides a management method of a student growth file, which comprises a face recognition step, a picture signal and a character signal which are uploaded by a user are received; extracting a face characteristic value in the picture signal; judging whether the face characteristic value is matched with the target identity signal; if the face characteristic value is matched with the target identity signal, extracting keywords in the character signal, and matching intelligent categories according to the keywords; adding an intelligent class to the target profile signal.

Therefore, the information on the picture is acquired through face recognition, the face on the picture is recognized accurately and rapidly, the matched intelligent class is associated with the target after face recognition through extracting the keywords in the character signals added during picture uploading, the purpose of classifying the student files through the uploaded signals can be achieved simply and efficiently, and the error rate during classification is further reduced.

The use method comprises the steps that the picture signal comprises a plurality of face characteristic values; the step of judging whether the face characteristic value is matched with the target identity signal is as follows: outputting a plurality of target identity signals matched with the plurality of face characteristic values; outputting a signal to be confirmed; a user confirmation signal is received.

Therefore, the picture is not limited to only one target student, and when a plurality of face feature values appear, the correctness of the archive signal is further ensured through the confirmation of the user.

Further, the using method comprises an initialization step, and the initialization step comprises the following steps: an identity signal acquisition step and an intelligent type acquisition step; the identity signal acquisition step comprises the following steps: receiving a user registration signal and an uploaded identity photo; extracting an original face characteristic value in the identity photo; correlating the original face characteristic value with the registration signal, and storing the generated identity signal; the intelligent category acquisition step comprises: receiving intelligent classification uploaded by a user; receiving definition of intelligent classification by a user; and associating the definition with the intelligent category to generate an intelligent category storage.

Therefore, in the initialization step, the identity signal generated after the original face characteristic value is associated with the registration signal is stored, and the intelligent category generated after the intelligent classification and definition are associated is stored, so that the comparison between the face characteristic value of the received picture signal and the keyword of the received character signal is facilitated, and the effective management of the student growth file classification is facilitated.

Further, the using method further comprises an information management step, and the information management step comprises the following steps: acquiring a new identity photo and extracting a new face characteristic value; replacing the original face characteristic value with the new face characteristic value; acquiring a new registration signal of a user, and replacing the new registration signal with the registration signal; the new face characteristic value is associated with the new registration signal to generate a new identity signal to be stored; and executing a face recognition step.

Therefore, the information management step enables the information of the students to be updated, the accuracy of the face recognition system is further improved, and the accuracy of student growth file management is further improved.

Further, the management method further comprises: and calculating the growth capacity according to the target file signals.

Therefore, through calculation and analysis of the target archive signals, the target identity signals and the intelligent categories, the conclusion that the growth capacity of the target students is high is obtained, and then the method is beneficial to cultivation of students which are more specialized, and the teaching which is more beneficial to growth of the target students is converted through guidance of interest of the target students.

Further, the using method further comprises a safety protection step, wherein the safety protection step comprises the following steps: receiving a user login signal, wherein the login signal comprises a user name signal and a password signal; if the user name signal or the password signal is input wrongly, the user login signal is continuously received; and locking the user name signal when the password signal is input for the preset error times.

Therefore, the safety protection step is arranged, the safety performance of the using method is improved, the user needs to input the user name signal and the password signal at the same time during login, the user name signal is locked when the password signal input error frequency reaches the preset error frequency, the possibility that a non-user obtains student information is avoided, and meanwhile the possibility that the user mistakenly inputs the student information is also avoided.

In order to achieve the second object of the present invention, the computer apparatus according to the present invention includes a processor and a memory, wherein the memory stores a computer program, and the computer program implements the steps of the management method when executed by the processor.

In order to achieve the third object of the present invention, the present invention provides a computer-readable storage medium having stored thereon a computer program, which when executed by a controller, implements the steps of the above-described management method.

Drawings

FIG. 1 is a system diagram of a method for managing student growth profiles according to an embodiment of the present invention.

FIG. 2 is a flowchart of an embodiment of a student growth profile management method according to the invention.

Fig. 3 is a flowchart of the face recognition step of the embodiment of the student growth profile management method of the invention.

FIG. 4 is a flowchart illustrating the safety protection steps of the student growth profile management method according to an embodiment of the present invention.

FIG. 5 is a flowchart of the information management steps of the student growth profile management method according to an embodiment of the present invention.

The invention is further explained with reference to the drawings and the embodiments.

Detailed Description

The following embodiments take the management method of student growth files as an example, including but not limited to students, enterprise personnel growth files, family member growth files, and enterprise worker growth files. The growth file is not limited to the growth file, and may be a record of growth.

The embodiment of the management method of the student growth file comprises the following steps:

referring to fig. 1, the method for managing a student growth profile includes: an initialization step S1, a security step S2, a face recognition step S3, and an information management step S4.

Referring to fig. 2, an initialization step S1 is performed, the initialization step S1 including an identity signal acquisition step S11 and a smart category acquisition step S12;

first, an identification signal collecting step S11 is performed, where the identification signal collecting step S11 includes:

step S111 is executed, and a user registration signal and an uploaded identity photo are received;

step S112 is executed, and the original face characteristic value in the identity photo is extracted;

step S113 is executed, the original face characteristic value is associated with the registration signal, and the generated identity signal is stored; the user opens the system, inputs the registration signal in the system, the system receives the registration signal and simultaneously receives the identity photo uploaded by the user, the face information is obtained by extracting the face characteristic value, a face library is established, and simultaneously the identity signal is stored in the system.

Subsequently, a smart category collecting step S12 is performed, the smart category collecting step S12 including:

executing step S121, receiving the intelligent classification uploaded by the user;

executing step S122, receiving the definition of the intelligent classification by the user;

step S123 is executed, the definition is associated with the intelligent category, and the intelligent category is generated and stored; the user opens the system, inputs intelligent classification in the system, and intelligent classification divides into nine major categories in this embodiment, is respectively: language intelligence, mathematical logic intelligence, space intelligence, limb kinesthetic intelligence, music intelligence, interpersonal intelligence, introspection intelligence, natural intelligence, and intelligent intelligence. The system receives the nine intelligent classifications and simultaneously receives the definition of the intelligent classification by the user.

The definition of the Chinese intelligence is: including the ability of oral language application and character writing, combining syntax, phonology, semantics and language practicality and freely applying. Such people think in words and words while learning, and like word games, reading, discussion and writing.

The mathematical logic intelligence is defined as: people who work with numbers specifically need such intelligence to effectively exercise numbers and reasoning. They learn to think by reasoning, like to ask questions and perform experiments to seek answers, and to find the rules and logic sequences of things, and are interested in new developments in science. Even the talking behavior of others becomes a good way for them to find logical defects, and is more acceptable for things that can be measured, categorized, and analyzed.

The spatial intelligence is defined as: people with strong spatial intelligence have high sensitivity to colors, lines, shapes, forms, spaces and relations among the colors, the lines, the shapes, the forms and the spaces, can accurately sense visual spaces and express the sensed spaces. Such people think with images and images while learning.

The definition of the kinesthetic intelligence of the limb is: it is good at using the whole body to express thoughts and feelings, and the ability to use both hands to create or modify things with dexterity. Such people are difficult to sit still for long periods of time, like to build things with hands, like outdoor activities, often using gestures or other body language when talking to a person. They learn to think through physical sensation.

The definition of musical intelligence is: people with strong intelligence can perceive, distinguish, change and express music, and have sensitivity to rhythm, tone, melody or tone. During learning, the rhythm melody is considered. Interpersonal intelligence is defined as the sensitivity of such people to human facial expressions, sounds and actions, and the ability to perceive and distinguish the mood, intent, motivation and sensation of others. They prefer to participate in group-like activities, and to find others to help or teach people how to do so, which is comfortable among the population. They are usually the leaders in the group, thinking with feedback from others. Such as canary, black young dragon, rossofu.

The definition of introspection intelligence is: people with high intelligence in the province can understand themselves, realize the inherent emotion, intention, motivation, splenic qi and desire, and the abilities of self-discipline, self-knowledge and self-respect. They can learn about their merits from various feedback pipelines, and think to plan their life objectives, love the independence, and think deeply in our way. Introspection intelligence can be divided into two levels: an event hierarchy and a value hierarchy. Introspection of the event hierarchy points to a summary of the success or failure of an event, and introspection of the value hierarchy connects the success or failure of an event with the value view from the review.

The natural intelligence is defined as: the ability of plants, animals and other natural environments (such as clouds and stones) can be appreciated. People with strong natural intelligence have more prominent performance in hunting, farming and bioscience. Natural intelligence should further be relegated to exploratory intelligence. Including both social and natural quests.

The definition of smart is: the thinking ability of universe and abstract life, and the inspiration, the thinking ability and the intuitive thinking ability of things essence. And establishing an intelligent classification library, and storing the intelligent classification into the system.

Referring to fig. 3, when all the identity signals and the intelligent categories are stored in the system, the process proceeds to a security step S2, where the security step S2 includes:

executing step S21, receiving user login signal;

step S22 is executed to determine whether the login signal is correct;

if the login signal is correct, executing step S23, and the user successfully logs in;

step S24 is executed, and a user uploading interface is entered;

if the login signal is input incorrectly, executing step S221, determining whether the login signal is input incorrectly three times, if the login signal is input incorrectly three times, executing step S222, and locking the login signal of the user; if the logged signal is not inputted with an error three times, the process proceeds to step S21.

After entering the user uploading interface, the user inputs date and activity in the uploading interface, and the options of the activity are as follows: singing games, class basketball games, common sense question and answer games, school meetings and the like, clicking the option of uploading pictures, selecting the pictures to be uploaded, entering an uploading activity interface, adding the pictures to be uploaded and corresponding activity descriptions of the pictures, referring to fig. 4, executing a face recognition step S3 by the system, wherein the face recognition step S3 comprises:

executing step S31, receiving picture signals and character signals uploaded by a user;

executing step S32, extracting the face characteristic value in the picture signal;

step S33 is executed, and whether the face characteristic value is matched with the target identity signal is judged;

if not, executing step S331, outputting a picture signal error;

if so, executing step S34 to output a plurality of identity signals matching with the face feature values; for example, receiving a picture uploaded by a user, wherein the picture contains head portraits of a plurality of students, extracting a face feature value in each head portrait by the system to be matched with a face feature value in an initially established face library to obtain identity signals of the plurality of students, and then displaying the related face pictures.

And step S35 is executed, the uploading confirmation signal is received, the user screens whether the student corresponding to the face needs to be recorded in the corresponding file again according to the displayed face picture, and the uploading is checked and confirmed.

Executing step S36, extracting keywords in the text signal;

executing step S37, judging whether the keyword is matched with the intelligent category signal;

if the matching is judged, executing step S38 to add the matched intelligent type signal to the target file signal;

finally, step S39 is executed, and the growth capacity is calculated according to the target file signals; for example, with a preset time as a deadline, the method determines which intelligent class signal belongs to the largest number according to the stored intelligent class signals, and obtains an adaptive intelligent class of the corresponding target student, thereby further facilitating the learning planning of the target student.

Referring to fig. 5, when the user signal requires updating, the information managing step S4 is performed, and the information managing step S4 includes:

firstly, step S42 is executed to determine whether identity correction is required;

if yes, then step S43 is executed to obtain a new identity photo and extract a new face feature value;

then step S44 is executed, the new face characteristic value is replaced by the original target face characteristic value;

secondly, step S45 is executed to obtain a new registration signal of the user;

then executing step S46 to replace the original target registration signal with the new registration signal;

finally, step S47 is executed to associate the new registration signal with the new face feature value and generate a new identity signal for storage. The information management steps can be used for correcting the original identity signals and adding the identity signals of newly-entered students.

The embodiment of the computer device comprises:

the computer device of this embodiment includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the steps of the method for using the finding device are implemented.

For example, a computer program may be partitioned into one or more modules that are stored in a memory and executed by a processor to implement the modules of the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device.

The Processor may be a Central Processing Unit (CPU), or may be other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, or the like. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center of the terminal device and connecting the various parts of the entire terminal device using various interfaces and lines.

The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a system required by at least one function (such as a face recognition step, a security protection step, an information management step, and the like), and the like; the storage data area may store data created according to use of the mobile phone. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

A computer-readable storage medium:

the computer program stored in the computer device may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the processes in the method according to the above embodiments may also be implemented by a computer program, which may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the above audio/video playing method.

Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals.

Claims

1. A management method of student growth files is characterized by comprising a face recognition step;

the face recognition step comprises:

receiving picture signals and character signals uploaded by a user;

extracting a face characteristic value in the picture signal;

judging whether the face characteristic value is matched with a target identity signal;

if the face characteristic value is matched with the target identity signal, extracting keywords in the character signal, and matching intelligent categories according to the keywords;

adding the intelligent class to a target profile signal.

2. The management method according to claim 1, characterized in that:

the picture signal comprises a plurality of face characteristic values;

the step of judging whether the face characteristic value is matched with the target identity signal is as follows:

outputting a plurality of the target identity signals matched with a plurality of the face characteristic values;

outputting a signal to be confirmed;

receiving the user confirmation signal.

3. The management method according to claim 1, characterized in that:

the method of use comprises an initialization step comprising: an identity signal acquisition step and an intelligent type acquisition step;

the identity signal acquisition step comprises:

receiving the user registration signal and the uploaded identity photo;

extracting an original face characteristic value in the identity photo;

correlating the original face characteristic value with the registration signal, and storing the generated identity signal;

the intelligent category collecting step comprises:

receiving the intelligent classification uploaded by the user;

receiving a definition of the intelligent classification by the user;

and associating the definition with the intelligent category to generate an intelligent category storage.

4. The management method according to claim 1, characterized in that:

the use method further includes an information management step including:

acquiring a new identity photo and extracting a new face characteristic value;

replacing the original face characteristic value with the new face characteristic value;

acquiring a new registration signal of a user, and replacing the registration signal with the new registration signal;

the new face characteristic value is associated with the new registration signal to generate a new identity signal to be stored;

and executing the face recognition step.

5. The management method according to claim 1, characterized in that:

the management method further comprises the following steps:

and calculating the growth capacity according to the target file signals.

6. The management method according to any one of claims 1 to 5, characterized in that:

the using method further comprises a safety protection step, wherein the safety protection step comprises the following steps:

receiving the user login signal, wherein the login signal comprises a user name signal and a password signal;

if the user name signal or the password signal is input wrongly, the user login signal is continuously received;

and locking the user name signal when the password signal is input for the preset error times.

7. A computer arrangement, characterized in that the computer arrangement comprises a processor for implementing a method of use according to any of claims 1 to 6 when executing a computer program stored in a memory.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when executed by a processor, implements a method of use as claimed in any one of claims 1 to 6.